• Journal of the Institute of Convergence Signal Processing
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• v.11 no.4
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• pp.338-344
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• 2010

Both ends of welding line are often closed by wall in the welding of ship blocks. In this research, seam tracking sensing system for butt welding in the condition with wall was developed. Seam tracking sensing system measures position of carriage from wall and detects root-pass of welding line. The system consists of the laser displacement sensors and ultrasonic sensors. The laser displacement sensor reciprocal1y rotates by the motor and measures a distance from laser sensor to the welding material. The ultrasonic sensor measures a distance between welding system and walls. The distance measured by the ultrasonic sensor is used to get X(driving) position and to determine initial and end point of the weld line. Y(weaving) and Z(height) of the weld line are obtained by the distance measured by the laser displacement sensor and the orientation of the sensor. The sensing system includes the controller that is independent from the welding carriage. The seam tracking sensing system is attached to both side of welding carriage so that interference between welding torch and sensing system can be avoided during the welding. And both side sensing system minimize dead zone. Finally, developed sensing system was adhered to welding carriage and verified usefulness by experiments.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.4
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• pp.389-394
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• 2023

In recent years, use of machine automation is rising in the industry. Ships also obtain machine condition information from sensor as digital information. However, on ships, crew members regularly surveil the engine room to check the condition of equipment and their information through analog gauges. This is a time-consuming and tedious process and poses safety risks to the crew while on surveillance. To address this, engine room surveillance using an autonomous mobile robot is being actively explored as a solution because it can reduce time, costs, and the safety risks for crew. Analog gauge reading using an autonomous mobile robot requires digitization for the robot to recognize the gauge value. In this study, image processing techniques were applied to achieve this. Analog gauge images were subjected to image preprocessing to remove noise and highlight their features. The center point, indicator point, minimum value and maximum value of the analog gauge were detected through image processing. Through the straight line connecting these points, the angle from the minimum value to the maximum value and the angle from the minimum value to indicator point were obtained. The obtained angle is digitized as the value currently indicated by the analog gauge through a formula. It was confirmed from the experiments that the digitization of the analog gauge using image processing was successful, indicating the equivalent current value shown by the gauge. When applied to surveillance robots, this algorithm can minimize safety risks and time and opportunity costs of crew members for engine room surveillance.